Semantic Web - Volume 9, issue 6

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ISSN 1570-0844 (P)
ISSN 2210-4968 (E)

Impact Factor 2018: 2.224

The journal Semantic Web – Interoperability, Usability, Applicability is an international and interdisciplinary journal bringing together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future Internet and elsewhere.

As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust and provenance core topics for Semantic Web research.

New retrieval paradigms, user interfaces and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. Papers which add a social, spatial and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics, are especially welcome.

Abstract: The built environment consists of plenty of physical assets with which we interact on a daily basis. In order to improve not only our built environment, but also our interaction with that environment, we would benefit a lot from semantic representations of this environment. This not only includes buildings, but also large infrastructure (bridges, tunnels, waterways, underground systems), and geospatial data. With this special issue, an insight is given into the current state of the art in terms of semantic technologies and interoperability in this built environment. This editorial not only summarizes the content of the Special Issue on Semantic…Technologies and interoperability in the Built Environment, it also provides a brief overview of the current state of the art in general in terms of standardisation and community efforts.
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Abstract: Fulfilling occupants’ comfort whilst reducing energy consumption is still an unsolved problem in most of tertiary buildings. However, the expansion of the Internet of Things (IoT) and Knowledge Discovery in Databases (KDD) techniques lead to research this matter. In this paper the EEPSA (Energy Efficiency Prediction Semantic Assistant) process is presented, which leverages the Semantic Web Technologies (SWT) to enhance the KDD process for achieving energy efficiency in tertiary buildings while maintaining comfort levels. This process guides the data analyst through the different KDD phases in a semi-automatic manner and supports prescriptive HVAC control strategies. That is, temperature of a…space is predicted simulating the activation of HVAC systems at different times and intensities, so that the facility manager can choose the strategy that best fits both the user’s comfort needs and energy efficiency. Furthermore, results show that the proposed solution improves the accuracy of predictions.
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Abstract: Energy consumption and performance assessment of Smart Cities must consider different levels and various sub-domains. A comprehensive energy profile of a city, in fact, should work at the city, district, and building levels. At the same time and for each level, it should take into account both electrical and thermal consumptions, and gather these information from a plethora of different sensors and from various stakeholders (i.e., citizens, utilities, policy makers, and energy providers). Current modeling approaches for this context address each level and domain separately, thus preventing a structured and comprehensive approach to a unified energy representation. Moreover, current approaches…make it difficult to keep the consistency between the energetic data through levels, sub-domains, and across stakeholders. Starting from an analysis of ontologies at the state-of-the-art, this paper shows how DogOnt can be used as a foundation towards a shared and unified model for such a context. DogOnt was firstly developed in 2008 and withstands over 8 years of usage without major failures and shortcomings. We discuss successful design choices and adaptations, which kept the model up-to-date and increasingly adopted in such a mid-term time frame for energy representation in Smart Cities.
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Abstract: Ambient Intelligence aims at simplifying the interaction of a user with her surrounding context, minimizing the effort needed to increase comfort and assistance. Nevertheless, especially in built and structured environments, current technologies and market solutions are often far from providing the required levels of automation, coordination and adaptivity. Devices should interact autonomously, should reach opportunistic decisions and take actions accordingly. In particular, user activities and profiles should be among the manifold implicit factors to be taken into account in that process. Home and Building Automation (HBA) is one of the most relevant scenarios suffering from the poorness of the…allowed system intelligence, automation and adaptivity. Devices are logically associated through static profiles defined at system deployment stage. The large majority of solutions are proprietary and centralized, and require manual configuration. This paper proposes a novel semantic-based framework complying with the emerging Social Internet of Things paradigm. Infrastructured spaces can be intended as populated by device agents organized in social networks, interacting autonomously and sharing information, cooperating and orchestrating resources. A service-oriented architecture allows collaborative dissemination, discovery and composition of service/resource descriptions. Semantic Web languages are adopted as knowledge representation layer and mobile-oriented implementations of non-monotonic inferences for semantic matchmaking are used to give decision capabilities to software agents. Finally, the Linked Data Platform (LDP) over the Constrained Application Protocol (CoAP) provides the knowledge organization and sharing infrastructure underpinning social object interactions. The framework has been implemented and tested in a home automation prototype integrating several communication protocols and off-the-shelf devices. Experiments advocate the effectiveness of the approach.
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Abstract: The contextual information in the built environment is highly heterogeneous, it goes from static information (e.g. , information about the building structure) to dynamic information (e.g. , user’s space–time information, sensors detections and events that occurred). This paper proposes to semantically fuse the building’s contextual information with extracted data from a smart camera network by using ontologies and semantic web technologies. The developed ontology allows interoperability between the different contextual data and enables, without human interaction, real-time event detections and system reconfiguration to be performed. The use of semantic knowledge in multi-camera monitoring systems guarantees the protection of the user’s…privacy by not sending nor saving any image, just extracting the knowledge from them. This paper presents a new approach to develop an “all-seeing” smart building, where the global system is the first step to attempt to provide Artificial Intelligence (AI) to a building.
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Abstract: In this paper, we propose to extend SPARQL functions for querying Industry Foundation Classes (IFC) building data. The official IFC documentation and BIM requirement checking use cases are used to drive the development of the proposed functionality. By extending these functions, we aim to (1) simplify writing queries and (2) retrieve useful information implied in 3D geometry data according to requirement checking use cases. Extended functions are modelled as RDF vocabularies and classified into groups for further extensions. We combine declarative rules with procedural programming to implement extended functions. Realistic requirement checking scenarios are used to evaluate and demonstrate the…effectiveness of this approach and indicate query performance. Compared with query techniques developed in the conventional Building Information Modeling domain, we show the added value of such approach by providing an application example of querying building and regulatory data, where spatial and logic reasoning can be applied and data from multiple sources are required. Based on the implementation and evaluation work, we discuss the advantages and applicability of this approach, current issues and future challenges.
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Abstract: The increasing adoption of the Linked Data principles brought with it an unprecedented dimension to the Web, transforming the traditional Web of Documents to a vibrant information ecosystem, also known as the Web of Data. This transformation, however, does not come without any pain points. Similar to the Web of Documents, the Web of Data is heterogenous in terms of the various domains it covers. The diversity of the Web of Data is also reflected in its quality. Data quality impacts the fitness for use of the data for the application at hand, and choosing the right dataset is…often a challenge for data consumers. In this quantitative empirical survey, we analyse 130 datasets (≈ 3.7 billion quads), extracted from the latest Linked Open Data Cloud using 27 Linked Data quality metrics, and provide insights into the current quality conformance. Furthermore, we publish the quality metadata for each assessed dataset as Linked Data, using the Dataset Quality Vocabulary (daQ). This metadata is then used by data consumers to search and filter possible datasets based on different quality criteria. Thereafter, based on our empirical study, we present an aggregated view of the Linked Data quality in general. Finally, using the results obtained from the quality assessment empirical study, we use the Principal Component Analysis (PCA) test in order to identify the key quality indicators that can give us sufficient information about a dataset’s quality.
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Abstract: In this article we outline the details of an ontology, called SmartEnv, proposed as a representational model to assist the development process of smart (i.e., sensorized) environments. The SmartEnv ontology is described in terms of its modules representing different aspects including physical and conceptual aspects of a smart environment. We propose the use of the Ontology Design Pattern (ODP) paradigm in order to modularize our proposed solution, while at the same time avoiding strong dependencies between the modules in order to manage the representational complexity of the ontology. The ODP paradigm and related methodologies enable incremental construction of ontologies by…first creating and then linking small modules. Most modules (patterns) of the SmartEnv ontology are inspired by, and aligned with, the Semantic Sensor Network (SSN) ontology, however with extra interlinks to provide further precision and cover more representational aspects. The result is a network of 8 ontology patterns together forming a generic representation for a smart environment. The patterns have been submitted to the ODP portal and are available on-line at stable URIs.
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